An analysis of the Corporate Manslaughter and Corporate Homicide Act (2007): A Badly Flawed Reform?
Bibliographic record
Abstract
A conviction of a large corporation for manslaughter was in practice impossible. This statement was accurate when the prosecution utilised the identification/ “directing mind and will” doctrine. The position in relation to prosecutions against small companies was somewhat different. It was relatively straight-forward to successfully prosecute a “one-man band” style company due to its simple corporate structure. The Corporate Manslaughter and Corporate Homicide Act (2007) was enacted to resolve this issue. This thesis will endeavour to consider the lengthy process of law reform that ultimately resulted in the enactment of the legislation. It was the desire of Parliament that this Act would eliminate the difficulties that were faced by the courts when dealing with large complex corporate structures. This thesis will consider whether Parliament’s desire has been achieved or whether the same problems associated with the old doctrine still exist. This thesis will argue that the Corporate Manslaughter and Corporate Homicide Act (2007) has simply provided a gloss upon the identification doctrine and that we now have an “identification-plus” doctrine in the form of the “senior management test”. It is therefore questionable whether the new test would be any more effective when tested against a large corporate structure, than the old doctrine. In addition, this thesis will consider the Canadian model and whether any lessons can be learned from their approach to corporate criminal liability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".